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生态环境治理中人工智能的融入路径研究 被引量:1

Research on the Integration Path of Artificial Intelligence in Ecological Environment Governance
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摘要 过去数十年间,我国经济长期保持高速增长的态势,但也出现了发展不平衡、不可持续等问题,面临着较为严峻的环境污染现象,对社会可持续发展、民众生活品质等造成了不良的影响。随着生态文明建设的逐步深入,生态环境治理成效得到显著改善,促进了人类社会的可持续发展。但在传统生态环境治理的实践中,也暴露出诸多的问题与不足,与新时代生态环境建设要求存在差距。而通过在生态环境治理中融入人工智能,可更加高效地配置生态资源,改善生态环境治理成效。因此,相关人员要充分认识到人工智能对生态文明建设的重要促进作用,于生态环境治理中科学融入人工智能,在提升生态环境治理效率的基础上,加快我国生态文明建设步伐。 Over the past few decades, China’s economy has maintained a high-speed growth trend for a long time, but there have also been problems such as unbalanced and unsustainable development. It is facing a more severe phenomenon of environmental pollution, which has had a negative impact on social sustainable development and people’s quality of life. With the gradual deepening of the construction of ecological civilization, the effectiveness of ecological environment governance has been significantly improved,which has promoted the sustainable development of human society. However, in the practice of traditional ecological environment governance, many problems and deficiencies have also been exposed, which is far from the requirements of ecological environment construction in the new era. By integrating artificial intelligence into eco-environmental governance, we can more efficiently allocate ecological resources and improve the effectiveness of eco-environmental governance. Therefore, relevant personnel should fully realize the important role of artificial intelligence in promoting the construction of ecological civilization, scientifically integrate artificial intelligence into ecological environment governance, and speed up the construction of ecological civilization in China on the basis of improving the efficiency of ecological environment governance.
作者 张卉 Zhang Hui(Qinhuangdao Ecological Environment Bureau,Qinhuangdao 066000,China)
出处 《皮革制作与环保科技》 2022年第5期176-178,共3页 Leather Manufacture and Environmental Technology
关键词 生态环境治理 人工智能 融入路径 ecological environment management artificial intelligence integration path
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